Dipl.-Inf. Marvin Lindner
| email: | marvin.lindner@uni-siegen.de |
| phone: | +49 (271) 740-2794 |
| fax: | +49 (271) 740-3337 |
| address: | University of Siegen Faculty 12 FG Computer Graphics and Multimedia Systems Hölderlinstraße 3 57076 Siegen (Germany) |
Teaching
Research
3D Vision
A growing number of modern applications such as position determination, object recognition and collision prevention depend on accurate scene analysis. The estimation of an object's distance relative to an observers position by image analysis or laser scan techniques is thereby still the most time-consuming and expansive part.
A lower-priced and much faster alternative is the distance measurement with modulated, coherent infrared light based on the Photonic Mixer Device (PMD) technique.
Distance Calibration
This reasearch direction focuses on the design and evaluation of proper calibration models for the very complex and lightly explored distance mapping process of the PMD, which includes lateral and distance calibration by deviation analysis. Additional concepts combine PMD information with common highresolution 2D images in order to increase the distance resolution and accuracy for further image processing tasks in the context of computer vision.
Data Fusion
An important field of reasearch in computer vision is the 3D analysis and reconstruction of objects and scenes. Unfortunately, PMD-based devices have still limited resolution and provide only IR intensity information.
Data fusion focuses on a fast algorithmic approach to combine high resolution RGB images with PMD distance data, acquired using a binocular camera setup. The resulting combined RGBZ-data not only enhances the visual result, but also represents a basis for advanced data processing in e.g. object recognition with sub-pixel accuracy. A simple but efficient method is used to detect geometric occlusion caused by the binocular setup, which otherwise will lead to false color assignments.
Motion Compensation
Utilizing current Photo Mixing Detectors to acquire dynamic scenes introduces new problems in terms of motion artefacts. A phenomenon which is based on the internal imaging process of current Photo Mixing Detectors, incorporating four raw images to compute one distance image.
This research direction focuses on the design of accurate algorithms for the realtime compensation of motion artefacts.
Geometric Reconstruction
Current Photo Mixing Detectors acquire simple point clouds representing the scene from the observers point of view.
Geometric reconstruction focuses on the accurate visualization and the reconstruction of observed sceneries incooperating resolution refinement, GPU-based surface estimation as well as object segmentation.
Publications
Articles in Journals
| · | M. Lindner, M. Lambers, A. Kolb |
| Data Fusion and Edge-Enhanced Distance Refinement for 2D RGB and 3D Range Images | |
| In in Int. J. on Intell. Systems and Techn. and App. (IJISTA), Issue on Dynamic 3D Imaging, 5(1), 2008, pages 344 - 354 | |
| [bib] [pdf] |
Peer-Reviewed Papers
| · | Marvin Lindner, Andreas Kolb |
| Lateral and Depth Calibration of PMD-Distance Sensors | |
| In in Advances in Visual Computing, Springer, 2, 2006, pages 524-533 | |
| [bib] [pdf] |
| · | M. Lindner, A. Kolb |
| Calibration of the intensity-related distance error of the PMD TOF-Camera | |
| In in SPIE: Intelligent Robots and Computer Vision XXV, 6764, 2007, pages 6764-35 | |
| [bib] [pdf] |
| · | M. Lindner, A. Kolb |
| Data-Fusion of PMD-Based Distance-Information and High-Resolution RGB-Images | |
| In in Proc. of the Int. IEEE Symp. on Signals, Circuits & Systems (ISSCS), 1, 2007, pages 121 - 124 | |
| [bib] [pdf] |
| · | M. Lindner, A. Kolb, T. Ringbeck |
| New Insights into the Calibration of TOF Sensors | |
| In in IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Workshop on ToF Camera based Computer Vision (TOF-CV), 2008, pages 1-5 | |
| [bib] [pdf] |

